School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China, No. 2006 Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, PR China; State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, China, No. 225 Guangzhou Road, Nanjing 210029, PR China.
School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China, No. 2006 Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, PR China.
Sci Total Environ. 2019 Apr 1;659:732-745. doi: 10.1016/j.scitotenv.2018.12.290. Epub 2018 Dec 28.
In this study, we propose to assess climate impact on forest cover (represented by EVI) at multiple scales in areas undergoing substantial land cover change, using Landsat imagery with human-induced land cover change effect excluded. Taking the Qingliu River catchment located in a subtropical humid monsoon area in China as a case study, the results indicate that EVI increases significantly (p < 0.01) during 1989-2014 with a magnitude of 0.026/decade. Spatial distribution of EVI is distinct in summer and growing season. Temperature and precipitation show high partial correlations with EVI, with better partial correlation found between EVI and temperature. Their partial correlations with EVI on monthly scale are higher than those on annual scale. Besides, precipitation and pan evaporation show accumulative lag effects (4 months) on forest EVI, while temperature has no lag effect. Finally, an empirical formula is established to quantify the relationship among EVI and its main driving factors (temperature and precipitation) by considering the precipitation threshold (200 mm). The findings should provide scientific supports for local forest management and ecosystem services, and should also support the hydrological effect assessment of vegetation cover change under climate change for the study area.
在这项研究中，我们拟采用 Landsat 影像，排除人为土地覆盖变化的影响，在经历大规模土地覆盖变化的地区，以多个尺度评估气候对森林覆盖（以 EVI 表示）的影响。以中国亚热带湿润季风区清流河流域为例，结果表明，1989-2014 年间 EVI 显著增加（p < 0.01），每十年增加 0.026。EVI 在夏季和生长季的空间分布特征明显。温度和降水与 EVI 呈高度偏相关，EVI 与温度的偏相关更好。它们与 EVI 的月尺度偏相关高于年尺度偏相关。此外，降水和潜在蒸散对森林 EVI 有 4 个月的累积滞后效应，而温度没有滞后效应。最后，通过考虑降水阈值（200 mm），建立了一个经验公式来量化 EVI 及其主要驱动因素（温度和降水）之间的关系。这些发现为当地森林管理和生态系统服务提供了科学支持，也为研究区植被覆盖变化的水文效应评估提供了支持。
